Fix your tools

Posts — Table Of Contents

Demystifying Debuggers Series

lala-hakobyan/front-end-debugging-handbook

A comprehensive guide to debugging tools for modern, complex front-end applications. This handbook provides practical, real-world guidance on a complete suite of tools, from Chrome DevTools and framework extensions to integrated IDE debuggers.

[bug] tauri build errors out at bundling step · Issue #5175 · tauri-apps/tauri

Describe the bug When running tauri build the binary builds fine but then immediately errors out with thread '<unnamed>' panicked at 'Can't detect any appindicator library&#39...

Exult

Since the 1.12.0 release we fixed some crashes and a plot stopping bug which warrant a hotfix release. Our new stable build has these fixes applied:

Exult

Since the 1.12.0 release we fixed some crashes and a plot stopping bug which warrant a hotfix release. Our new stable build has these fixes applied:

Snowflake Cortex AI Escapes Sandbox and Executes Malware

PromptArmor report on a prompt injection attack chain in Snowflake's Cortex Agent, now fixed. The attack started when a Cortex user asked the agent to review a GitHub repository that …

Segfaults are our friends and teachers

This afternoon, I got a segmentation fault in a Rust program, and was confused. This is Rust, I shouldn’t get segfaults! I quickly checked the couple of places I used unsafe, and they were either calling C functions (and checking the errors), or telling the compiler not to initialize some memory because I was going to write into it unconditionally before reading from it.

Flawless - Durable Execution Engine

Flawless is an execution engine for durable computation. It will run your code until completion even in the presence of hardware or software failure.

SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks

Software development is iterative, yet agentic coding benchmarks overwhelmingly evaluate single-shot solutions against complete specifications. Code can pass the test suite but become progressively harder to extend. Recent iterative benchmarks attempt to close this gap, but constrain the agent’s design decisions too tightly to faithfully measure how code quality shapes future extensions. We introduce SlopCodeBench, a language-agnostic benchmark comprising 20 problems and 93 checkpoints, in which agents repeatedly extend their own prior solutions under evolving specifications that force architectural decisions without prescribing internal structure. We track two trajectory-level quality signals: verbosity, the fraction of redundant or duplicated code, and structural erosion, the share of complexity mass concentrated in high-complexity functions. No agent solves any problem end-to-end across 11 models; the highest checkpoint solve rate is 17.2%. Quality degrades steadily: erosion rises in 80% of trajectories and verbosity in 89.8%. Against 48 open-source Python repositories, agent code is 2.2x more verbose and markedly more eroded. Tracking 20 of those repositories over time shows that human code stays flat, while agent code deteriorates with each iteration. A prompt-intervention study shows that initial quality can be improved, but it does not halt degradation. These results demonstrate that pass-rate benchmarks systematically undermeasure extension robustness, and that current agents lack the design discipline iterative software development demands.

Just a rumour of a bug is enough to find a security exploit these days

Thinking through how the conventional OSS security embargoes no longer buy us time, and what open source maintainers might do instead to respond

threddyrex/rustproto

atproto PDS and debugging tools

Report on Burnout in Open Source Software

I am currently working on a report on the causes of burnout in open source software, and am inviting the OSS community to share their thoughts!

Durable Execution Solutions

Build invincible apps with Temporal's open source durable execution platform. Eliminate complexity and ship features faster. Talk to an expert today!

SlopCodeBench: Benchmarking How Coding Agents Degrade Over Long-Horizon Iterative Tasks

Software development is iterative, yet agentic coding benchmarks hide design issues through their single-shot setup. Recent iterative benchmarks attempt to remedy this but heavily constrain an agent's design decision space, making it impossible to faithfully measure how their decisions shape future extensions. We introduce SlopCodeBench, a benchmark of 36 problems and 196 checkpoints where agents repeatedly extend their own solutions. Unlike prior iterative benchmarks, our evolving specifications demand architectural decisions but leave internal structure to the agent. We measure two forms of degradation: structural erosion (concentrated complexity) and verbosity (redundant code). Evaluating 15 coding agents across open and closed models, we find that no agent fully solves any problem end-to-end, and the best agent passes 14.8% of checkpoints. Quality degrades across checkpoints, with structural erosion rising in 77% of trajectories and verbosity in 75.5%. Compared to 473 open-source Python repositories, agent code is 2.3x more verbose and 2.0x more eroded, and the human repositories degrade less often and by smaller margins across their git histories. Explicit quality guidance reduces initial verbosity and erosion by up to a third, without affecting degradation rates. SlopCodeBench provides the first measurement of code degradation under iterative extension, revealing that agents pass checkpoints while producing code that erodes and bloats with each turn.